In many cases of digital image processing, several scaled versions of the initial image are used for the pattern recognition. An example for such a pattern recognizer is the classifier according to Viola-Jones, which is trained for a specific model size.
Depending on which distance the searched pattern (e.g. face or eye) has towards the camera system, a greater or smaller display occurs. Due to the fixed model size of the classifier, thus, it has to be searched in several scaling stages of the recorded image in order to obtain in one of the scaling stages an optimal accordance with the model size of the classifier. The scaling stages are normally searched ascendingly or descendingly (cf. image pyramid). This sequential processing is in particular very poorly suited for parallel architectures (e.g. FPGA).
Therefore, there is the need for an improved concept.